The Camel DSL partly tries to mimic a functional programming style without being able to offer application developers the full power of a functional programming language.

Scalaz-Camel is a new project that provides an alternative DSL
to Camel’s existing Java DSL and Scala DSL, but what advantages
does Scalaz-Camel have over the existing DSLs? JAXenter spoke to
Talend software architect and Scalaz-Camel owner Martin
Krasser.

JAXenter: What is the scalaz-camel project?

Martin Krasser: The scalaz-camel project is an attempt to combine enterprise integration patterns (EIPs) with functional
programming (FP): integration solutions are composed from EIPs with
a functional domain-specific language (DSL) that is based on the
Scala programming language and the Scalaz
functional programming library. For providing connectivity to other
systems over different protocols and APIs, scalaz-camel uses the
integration components from Apache Camel.

The scalaz-camel DSL is a set of combinators and composition
operators, used to compose message processors and messaging
endpoints to complete message processing routes. Components of
message processing routes can be plain Scala functions, existing
Camel message processors and endpoints as well as other routes or
route fragments. Composition flexibility, extensibility of the DSL
and idiomatic use of Scala and Scalaz have been important aspects
in the design of the scalaz-camel DSL.

Further key features are support for non-blocking routing and
asynchronous message processors. This was achieved with a
continuation-passing style (CPS) API. CPS is mainly used
internally, the DSL supports direct-style programming. Scalaz-camel
also uses concurrency strategies to abstract over the way how
messages are routed concurrently. Applications can either choose
from a number of predefined concurrency strategies or implement
highly specialized custom strategies, if needed. Configurable
concurrency strategies and support for non-blocking routing are
important prerequisites for building highly scalable and concurrent
integration solutions.

Furthermore, messages are immutable objects in scalaz-camel so
that they can be easily shared by concurrent messages processors.
The project also provides a bridge to the mutable counterparts in
Camel which allows a reuse of all existing Camel message processors
and components/endpoints in scalaz-camel applications.

A more detailed overview of scalaz-camel features is given in
the project’s Wiki,

JAXenter: How does the scalaz-camel DSL differ
from Camel’s existing Java DSL and Scala DSL?

Martin Krasser: Camel’s Java and Scala DSL is a
fluent API based on the builder pattern. In my opinion, the Camel
DSL partly tries to mimic a functional programming style without
being able to offer application developers the full power of a
functional programming language. This is where the scalaz-camel DSL
comes in. It fully leverages what Scala and Scalaz offers for
functional programming: message processors and endpoint producers
are (or can be converted to) first-class functions that can be
composed in a monadic or applicative way. Monadic composition with
the >=> operator is done for processors that depend on each
other such as message processors in a pipeline, whereas applicative
composition is done for message processors that can run independent
of each other such as the destinations in a recipient-list, for
example. For applicative composition, scalaz-camel offers special
combinators (multicast, scatter, …).

One doesn’t need to be an FP expert to use the scalaz-camel DSL.
Basic Scala knowledge is sufficient for getting started. This is
comparable to using Scala’s List or Option without needing to know
that these are monads.

Another important difference is that the scalaz-camel DSL is
extensible. Adding a new integration pattern is as simple as
defining a new function and importing that function. This allows,
for example, other libraries to easily contribute DSL extensions
from a subdomain, such as eHealth-Integration, without needing to
modify scalaz-camel itself. This is in contrast to the Camel DSL
which follows a more monolithic approach. Any extension to the DSL
must be made in the core of Apache Camel which is a limitation for
the evolution of other DSLs based on Apache Camel.

JAXenter: Can you give us an example use case
of Scalaz-Camel?

Martin Krasser: Both scalaz-camel and Apache
Camel can be used to achieve the same goal: construct integration
solutions by combining EIPs and other message processors to larger
message-processing applications. They only differ in their
programming paradigms and idioms, where scalaz-camel follows the
functional programming paradigm.

This means that all usage example of Apache Camel are also valid
usage examples of scalaz-camel. A simple scalaz-camel usage example from the order processing domain
is given in the project’s Wiki. It’s a tutorial for getting started
with scalaz-camel. Further usage examples are given in the
project’s test specifications.

JAXenter: What’s on your ‘to do’ list for the
project?

Martin Krasser: For the upcoming 0.3 release I
want to focus on the following items.

– Support for further enterprise integration patterns
– Support for transactions and redeliveries
– Akka integration
– More examples
– Performance profiling
– Documentation extensions
– Use of HawtDispatch

This list is preliminary. Any feedback, ideas and suggestions
for improvements are highly welcome and can be added to the
project’s issue tracker.

Martin Krasser is a software architect and programmer at Talend. His major interests are distributed systems, application integration and functional programming with focus on integration middleware and eHealth integration. He is active committer in several open source projects in the Scala and Java community.